# Gregory Ditzler

According to our database

^{1}, Gregory Ditzler## Timeline

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Book In proceedings Article PhD thesis Other## Links

#### On csauthors.net:

## Bibliography

2018

AKRON: An algorithm for approximating sparse kernel reconstruction.

Signal Processing, 2018

2017

Speeding up joint mutual information feature selection with an optimization heuristic.

Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

Fine tuning lasso in an adversarial environment against gradient attacks.

Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

Fraud Analysis Approaches in the Age of Big Data - A Review of State of the Art.

Proceedings of the 2nd IEEE International Workshops on Foundations and Applications of Self* Systems, 2017

High Performance Machine Learning (HPML) Framework to Support DDDAS Decision Support Systems: Design Overview.

Proceedings of the 2nd IEEE International Workshops on Foundations and Applications of Self* Systems, 2017

A fast information-theoretic approximation of joint mutual information feature selection.

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

A Self-Protection Agent Using Error Correcting Output Codes to Secure Computers and Applications.

Proceedings of the 2017 International Conference on Cloud and Autonomic Computing, 2017

Fraud Data Analytics Tools and Techniques in Big Data Era.

Proceedings of the 2017 International Conference on Cloud and Autonomic Computing, 2017

Autonomic Management of 3D Cardiac Simulations.

Proceedings of the 2017 International Conference on Cloud and Autonomic Computing, 2017

The AKRON-Kalman filter for tracking time-varying networks.

Proceedings of the 2017 IEEE EMBS International Conference on Biomedical & Health Informatics, 2017

2016

A study of an incremental spectral meta-learner for nonstationary environments.

Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

2015

A Bootstrap Based Neyman-Pearson Test for Identifying Variable Importance.

IEEE Trans. Neural Netw. Learning Syst., 2015

Learning in Nonstationary Environments: A Survey.

IEEE Comp. Int. Mag., 2015

Fizzy: feature subset selection for metagenomics.

BMC Bioinformatics, 2015

2014

Domain adaptation bounds for multiple expert systems under concept drift.

Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

Scaling a neyman-pearson subset selection approach via heuristics for mining massive data.

Proceedings of the 2014 IEEE Symposium on Computational Intelligence and Data Mining, 2014

Feature subset selection for inferring relative importance of taxonomy.

Proceedings of the 5th ACM Conference on Bioinformatics, 2014

2013

Incremental Learning of Concept Drift from Streaming Imbalanced Data.

IEEE Trans. Knowl. Data Eng., 2013

Incremental learning of new classes from unbalanced data.

Proceedings of the 2013 International Joint Conference on Neural Networks, 2013

Discounted expert weighting for concept drift.

Proceedings of the 2013 IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments, 2013

2012

Transductive learning algorithms for nonstationary environments.

Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

Forensic identification with environmental samples.

Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

Information theoretic feature selection for high dimensional metagenomic data.

Proceedings of the Proceedings 2012 IEEE International Workshop on Genomic Signal Processing and Statistics, 2012

2011

Semi-supervised learning in nonstationary environments.

Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

Hellinger distance based drift detection for nonstationary environments.

Proceedings of the 2011 IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments, 2011

2010

Incremental Learning of New Classes in Unbalanced Datasets: Learn

^{ + + }.UDNC.
Proceedings of the Multiple Classifier Systems, 9th International Workshop, 2010

An ensemble based incremental learning framework for concept drift and class imbalance.

Proceedings of the International Joint Conference on Neural Networks, 2010

An Incremental Learning Algorithm for Non-stationary Environments and Class Imbalance.

Proceedings of the 20th International Conference on Pattern Recognition, 2010

Optimal nu-SVM parameter estimation using multi objective evolutionary algorithms.

Proceedings of the IEEE Congress on Evolutionary Computation, 2010

Fusion methods for boosting performance of speaker identification systems.

Proceedings of the IEEE Asia Pacific Conference on Circuits and Systems, 2010